Risk Of Parkinson's Disease Research Articles

Exploring the Nicotine-Parkinson's disease link – Insights from the UK Biobank

IntroductionEvidence suggests an inverse correlation between smoking and Parkinson's disease (PD), yet the mechanisms remain unclear. This study examines the changing risk relationship between smoking and PD diagnosis using alcohol consumption, another reward-driven behavior, as a comparative measure. MethodsA nested case-control study was conducted using the UK Biobank (UKBB) database. Participants in the prediagnostic phase of PD were identified, and self-reported data on tobacco and alcohol use were analyzed employing conditional binary logistic regression. Polynomial and piece-wise regression models were employed to discern shifting associations with PD over time. ResultsOf 502,304 participants (63 ± 5.3 years, 63 % male), 3049 prediagnostic PD cases were identified. Non-smokers had a heightened PD risk, and this association strengthened closer to diagnosis. The odds ratio (OR [95 % CI]) associated with PD in non-smokers was 2.02 [1.07–3.81] 1–4 years before diagnosis, compared to 1.36 [1.02–1.83] at >10-year intervals (linear trend, p = 0.012). The time trajectory of ORs was best depicted by a quadratic function, identifying a shift in risk 7.5 years before diagnosis documentation. Similar patterns emerged among alcohol non-consumers, with an 8.5-year interval inflection point. ConclusionThis study identified two disparate risk trajectories among non-smokers: an initial low-amplitude increased risk at prolonged prediagnostic intervals possibly related to genetic/personality factors, followed by a sharp escalation in risk association commencing 7–8 years before diagnosis, possibly propelled by reverse causality. Similar trends in alcohol consumption reinforce these conclusions. These findings could suggest that smoking cessation may serve as an early indicator of PD.

Migraine and Risk of Parkinson Disease in Women: A Cohort Study.

Migraine and Parkinson disease (PD) are common neurologic disorders, which are hypothesized to share some pathophysiologic mechanisms. However, data on the association between migraine and risk of developing PD are sparse. We estimate the effect of migraine, migraine subtypes, and migraine episode frequency on the risk of developing PD in middle-aged and older women. We used data from the Women's Health Study, a United States-based cohort of women in health professions aged 45 years and older at baseline (1992-1995). Only women with complete self-reported information on migraine and headache and no history of PD were included. Participants were followed up for self-reported physician-diagnosed PD through December 31, 2021. We used multivariable Cox proportional hazards models to estimate hazard ratios (HRs) and corresponding 95% CIs of the association between migraine, migraine subtypes, and migraine episode frequency and the risk of developing PD. A total of 39,312 women were included in the analyses. Among those, 7,321 women (18.6%) reported any migraine at baseline, of whom 2,153 (5.5%) reported a history of migraine, 2,057 (5.2%) reported migraine with aura, and 3,111 (7.9%) reported migraine without aura. During a mean follow-up of 22.0 years, 685 PD cases were reported. Of those, 128 (18.7%) were reported by women who also reported any migraine and 557 (81.3%) by women without any migraine. After adjusting for confounding, the HR for the association of any migraine on the risk of PD was 1.07 (0.88-1.29). Compared with women without migraine, the HRs (95% CI) for PD were 0.87 (0.59-1.27) for migraine with aura, 1.21 (0.93-1.58) for migraine without aura, and 1.05 (0.76-1.45) for history of migraine. Compared with those with a migraine frequency of less than monthly, the HRs were 1.09 (0.64-1.87) for a monthly frequency and 1.10 (0.44-2.75) for a weekly or greater frequency. In this large cohort of women, the risk of developing PD was not elevated among those experiencing migraine, irrespective of migraine subtypes or the frequency of migraine. The generalizability of our findings to other populations, such as men, should be further investigated. ClinicalTrials.gov Identifier: NCT00000479.

Anemia, blood cell indices, genetic correlations, and brain structures: A comprehensive analysis of roles in Parkinson's disease risk

IntroductionAnemia may contribute significantly to the onset of Parkinson's disease (PD). Current research on the association between anemia and PD risk is inconclusive, and the relationships between anemia-related blood cell indices and PD incidence require further clarification. This study aims to investigate the relationships between anemia, blood cell indicators, and PD risk using a thorough prospective cohort study. MethodsWe used data from the UK Biobank, a prospective cohort study of 502,649 participants, and ultimately, 365,982 participants were included in the analysis. Cox proportional hazards models were utilized to adjust for confounding factors, aiming to thoroughly explore the associations between anemia and blood cell indices with the risk of incident PD. The interaction between anemia and Polygenic Risk Score (PRS) for PD was also examined. Linear regression and mediation analyses assessed potential mechanisms driven by brain structures, including grey matter volume. ResultsDuring a median follow-up of 14.24 years, 2513 participants were diagnosed with PD. Anemia considerably increased PD risk (hazard ratio [HR] 1.98, 95 % confidence interval [CI]: 1.81–2.18, P < 0.001) after adjustments. Those with high PRS for anemia had an 83 % higher PD incidence compared to low PRS participants. Sensitivity analyses confirmed result robustness. Linear regression showed that anemia correlated with grey matter volumes and most white matter tracts. Furthermore, mediation analyses identified that the volume of grey matter in Thalamus mediates the relationship between anemia and PD risk. ConclusionIn summary, we consider there to be a substantial correlation between anemia and increased PD risk.

Neuroanatomical and prognostic associations of depression in Parkinson’s disease

BackgroundDepression is reported as a risk factor, prodromal feature and late consequence of Parkinson’s disease (PD). We aimed to evaluate the timing, neuroanatomy and prognostic implications of depression in PD.MethodsWe...

Role of Glutathione in Parkinson's Disease Pathophysiology and Therapeutic Potential of Polyphenols.

Oxidative stress is recognized to have a central role in the initiation and progression of Parkinson's disease (PD). Within the brain, neurons are particularly sensitive to oxidation due in part to their weak intrinsic antioxidant defense. Theoretically, neurons mostly depend on neighboring astrocytes to provide antioxidant protection by supplying cysteine-containing products for glutathione (GSH) synthesis. Astrocytes and neurons possess several amino acid transport systems for GSH and its precursors. Indeed, GSH is the most abundant intrinsic antioxidant in the central nervous system. The GSH depletion and/or alterations in its metabolism in the brain contribute to the pathogenesis of PD. Noteworthy, polyphenols possess potent antioxidant activity and can augment the GSH redox system. Numerous in vitro and in vivo studies have indicated that polyphenols exhibit potent neuroprotective effects in PD. Epidemiological studies have found an association between the consumption of dietary polyphenols and a lower PD risk. In this review, we summarize current knowledge on the biosynthesis and metabolism of GSH in the brain, with an emphasis on their contribution and therapeutic potential in PD. In particular, we focus on polyphenols that can increase brain GSH levels against PD. Furthermore, some current challenges and future perspectives for polyphenol-based therapies are also discussed.

Gut-Brain Nexus: Mapping Multi-Modal Links to Neurodegeneration at Biobank Scale.

Alzheimer's disease (AD) and Parkinson's disease (PD) are influenced by genetic and environmental factors. Using data from UK Biobank, SAIL Biobank, and FinnGen, we conducted an unbiased, population-scale study to: 1) Investigate how 155 endocrine, nutritional, metabolic, and digestive system disorders are associated with AD and PD risk prior to their diagnosis, considering known genetic influences; 2) Assess plasma biomarkers' specificity for AD or PD in individuals with these conditions; 3) Develop a multi-modal classification model integrating genetics, proteomics, and clinical data relevant to conditions affecting the gut-brain axis. Our findings show that certain disorders elevate AD and PD risk before AD and PD diagnosis including: insulin and non-insulin dependent diabetes mellitus, noninfective gastro-enteritis and colitis, functional intestinal disorders, and bacterial intestinal infections, among others. Polygenic risk scores revealed lower genetic predisposition to AD and PD in individuals with co-occurring disorders in the study categories, underscoring the importance of regulating the gut-brain axis to potentially prevent or delay the onset of neurodegenerative diseases. The proteomic profile of AD/PD cases was influenced by comorbid endocrine, nutritional, metabolic, and digestive systems conditions. Importantly, we developed multi-modal prediction models integrating clinical, genetic, proteomic and demographic data, the combination of which performs better than any single paradigm approach in disease classification. This work aims to illuminate the intricate interplay between various physiological factors involved in the gut-brain axis and the development of AD and PD, providing a multifactorial systemic understanding that goes beyond traditional approaches.

Midnolin, a Genetic Risk Factor for Parkinson's Disease, Promotes Neurite Outgrowth Accompanied by Early Growth Response 1 Activation in PC12 Cells.

Parkinson's disease (PD) is an age-related progressive neurodegenerative disease. Previously, we identified midnolin (MIDN) as a genetic risk factor for PD. Although MIDN copy number loss increases the risk of PD, the molecular function of MIDN remains unclear. To investigate the role of MIDN in PD, we established monoclonal Midn knockout (KO) PC12 cell models. Midn KO inhibited neurite outgrowth and neurofilament light chain (Nefl) gene expression. Although MIDN is mainly localized in the nucleus, it does not encode DNA-binding domains. We therefore hypothesized that MIDN might bind to certain transcription factors and regulate gene expression. Of the candidate transcription factors, we focused on early growth response 1 (EGR1) because it is required for neurite outgrowth and its target genes are downregulated by Midn KO. An interaction between MIDN and EGR1 was confirmed by immunoprecipitation. Surprisingly, although EGR1 protein levels were significantly increased in Midn KO cells, the binding of EGR1 to the Nefl promoter and resulting transcriptional activity were downregulated as measured by luciferase assay and chromatin immunoprecipitation quantitative real-time polymerase chain reaction. Overall, we identified the MIDN-dependent regulation of EGR1 function. This mechanism may be an underlying reason for the neurite outgrowth defects of Midn KO PC12 cells.

Consensus Guidance for Genetic Counseling in GBA1 Variants: A Focus on Parkinson's Disease.

Glucocerebrosidase (GBA1) variants constitute numerically the most common known genetic risk factor for Parkinson's disease (PD) and are distributed worldwide. Access to GBA1 genotyping varies across the world and even regionally within countries. Guidelines for GBA1 variant counseling are evolving. We review the current knowledge of the link between GBA1 and PD, and discuss the practicalities of GBA1 testing. Lastly, we provide a consensus for an approach to counseling people with GBA1 variants, notably the communication of PD risk. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Sodium-glucose cotransporter 2 inhibitors and the risk of Parkinson disease in real-world patients with type 2 diabetes.

Diabetes increases the risk of Parkinson disease (PD). Sodium-glucose cotransporter 2 (SGLT2) inhibitors, a new glucose-lowering therapeutic class, have shown neuroprotective effects in mechanistic studies. However, the association between SGLT2 inhibitors and PD risk in real-world populations with type 2 diabetes (T2D) remains unclear. The aim was to assess the association between SGLT2 inhibitors and the risk of PD in older populations with T2D. This retrospective cohort analysis used Medicare claims data from 2016 to 2020 to identify fee-for-service beneficiaries ≥65 years diagnosed with T2D and without pre-existing PD. The initiation of an SGLT2 inhibitor was compared with that of a dipeptidyl peptidase-4 (DPP4) inhibitor. The outcome was the first incident PD ever since the date initiating either an SGLT2 inhibitor or a DPP4 inhibitor. We employed a 1:1 propensity score matching to balance the baseline covariates between treatment groups, including sociodemographics, comorbidities and co-medications. We applied Cox regression models to assess the effect of SGLT2 inhibitors versus DPP4 inhibitors on incident PD. Of 89 330 eligible Medicare beneficiaries (mean age: 75 ± 7 years, 52% women), 0.6% (n = 537) had incident PD over the follow-up. After 1:1 propensity matching, the PD incidence was 2.5 and 3.5 events per 1000 person-years in the SGLT2 inhibitor group and DPP4 inhibitor group, respectively. The SGLT2 inhibitor group was associated with a significantly lower risk of incident PD than the DPP4 inhibitor group (hazard ratio: 0.70 [95% confidence interval: 0.55-0.89]). There is a potential trend that the risk reduction in incident PD was profound in non-Hispanic Black individuals and insulin users. Compared to DPP4 inhibitors, SGLT2 inhibitors were associated with a significantly lower risk of incident PD in older populations with T2D.

Long-Term Dementia Risk in Parkinson Disease.

It is widely cited that dementia occurs in up to 80% of patients with Parkinson disease (PD), but studies reporting such high rates were published over two decades ago, had relatively small samples, and had other limitations. We aimed to determine long-term dementia risk in PD using data from two large, ongoing, prospective, observational studies. Participants from the Parkinson's Progression Markers Initiative (PPMI), a multisite international study, and a long-standing PD research cohort at the University of Pennsylvania (Penn), a single site study at a tertiary movement disorders center, were recruited. PPMI enrolled de novo, untreated PD participants and Penn a convenience cohort from a large clinical center. For PPMI, a cognitive battery is administered annually, and a site investigator makes a cognitive diagnosis. At Penn, a comprehensive cognitive battery is administered either annually or biennially, and a cognitive diagnosis is made by expert consensus. Interval-censored survival curves were fit for time from PD diagnosis to stable dementia diagnosis for each cohort, using cognitive diagnosis of dementia as the primary end point and Montreal Cognitive Assessment (MoCA) score <21 and Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part I cognition score ≥3 as secondary end points for PPMI. In addition, estimated dementia probability by PD disease duration was tabulated for each study and end point. For the PPMI cohort, 417 participants with PD (mean age 61.6 years, 65% male) were followed, with an estimated probability of dementia at year 10 disease duration of 9% (site investigator diagnosis), 15% (MoCA), or 12% (MDS-UPDRS Part I cognition). For the Penn cohort, 389 participants with PD (mean age 69.3 years, 67% male) were followed, with 184 participants (47% of cohort) eventually diagnosed with dementia. The interval-censored curve for the Penn cohort had a median time to dementia of 15 years (95% CI 13-15); the estimated probability of dementia was 27% at 10 years of disease duration, 50% at 15 years, and 74% at 20 years. Results from two large, prospective studies suggest that dementia in PD occurs less frequently, or later in the disease course, than previous research studies have reported.

Sex-Specific Imaging Biomarkers for Parkinson's Disease Diagnosis: A Machine Learning Analysis.

This study aimed to identify sex-specific imaging biomarkers for Parkinson's disease (PD) based on multiple MRI morphological features by using machine learning methods. Participants were categorized into female and male subgroups, and various structural morphological features were extracted. An ensemble Lasso (EnLasso) method was employed to identify a stable optimal feature subset for each sex-based subgroup. Eight typical classifiers were adopted to construct classification models for PD and HC, respectively, to validate whether models specific to sex subgroups could bolster the precision of PD identification. Finally, statistical analysis and correlation tests were carried out on significant brain region features to identify potential sex-specific imaging biomarkers. The best model (MLP) based on the female subgroup and male subgroup achieved average classification accuracy of 92.83% and 92.11%, respectively, which were better than that of the model based on the overall samples (86.88%) and the overall model incorporating gender factor (87.52%). In addition, the most discriminative feature of PD among males was the lh 6r (FD), but among females, it was the lh PreS (GI). The findings indicate that the sex-specific PD diagnosis model yields a significantly higher classification performance compared to previous models that included all participants. Additionally, the male subgroup exhibited a greater number of brain region changes than the female subgroup, suggesting sex-specific differences in PD risk markers. This study underscore the importance of stratifying data by sex and offer insights into sex-specific variations in PD phenotypes, which could aid in the development of precise and personalized diagnostic approaches in the early stages of the disease.

Anti-diabetic drug use and reduced risk of Parkinson's disease: A community-based cohort study

BackgroundEmerging evidence suggests a potential association between certain anti-diabetic drugs and a reduced risk of Parkinson's disease (PD). Limited population-based studies have investigated users of newer anti-diabetic drugs such as GLP-1 agonists or SGLT2 inhibitors. ObjectiveThe aim of this study was to assess the risk of PD among individuals with type 2 diabetes mellitus (T2DM) who were treated with various types of anti-diabetic drugs over time. MethodsA population-based cohort comprising T2DM patients aged over 30 who used metformin, GLP-1 agonists, thiazolidinediones, sulfonylureas, DPP4 inhibitors, SGLT2 inhibitors, or meglitinides between January 1, 1999 and December 31, 2018. Data were obtained between the diabetes registration and drug purchase databases of Maccabi Healthcare Services. Time-dependent Cox regression models, adjusted for sex, age, and comorbidities were employed to calculate the adjusted hazard ratios (HRs) for the PD risk associated with different anti-diabetic drugs over time. ResultsThe study population comprised 86,229 T2DM patients, with 53.9 % males. The mean age at the first anti-diabetic drug purchase was 59.0 ± 11.0 and 62.0 ± 11.0 years for men and women respectively. Compared to metformin, several drug types were associated with a significantly lower PD risk: thiazolidinediones (HR = 0.91, 95 % CI:0.074–1.14); DPP4 inhibitors (HR = 0.60, 95 % CI:0.53–0.67); meglitinides (HR = 0.63, 95 % CI:0.53–0.74); GLP-1 agonists (HR = 0.54, 95 % CI:0.39–0.73); and SGLT2 inhibitors (HR = 0.15, 95 % CI:0.10–0.21). ConclusionsOur results suggest a reduced risk of PD with certain anti-diabetic drugs, particularly SGLT2 inhibitors and GLP-1 agonists. Validation through extensive big-data studies is essential to confirm these results and to optimize PD prevention and management.

Identifying potential causal effects of Parkinson’s disease: A polygenic risk score-based phenome-wide association and mendelian randomization study in UK Biobank

There is considerable uncertainty regarding the associations between various risk factors and Parkinson’s Disease (PD). This study systematically screened and validated a wide range of potential PD risk factors from 502,364 participants in the UK Biobank. Baseline data for 1851 factors across 11 categories were analyzed through a phenome-wide association study (PheWAS). Polygenic risk scores (PRS) for PD were used to diagnose Parkinson’s Disease and identify factors associated with PD diagnosis through PheWAS. Two-sample Mendelian randomization (MR) analysis was employed to assess causal relationships. PheWAS results revealed 267 risk factors significantly associated with PD-PRS among the 1851 factors, and of these, 27 factors showed causal evidence from MR analysis. Compelling evidence suggests that fluid intelligence score, age at first sexual intercourse, cereal intake, dried fruit intake, and average total household income before tax have emerged as newly identified risk factors for PD. Conversely, maternal smoking around birth, playing computer games, salt added to food, and time spent watching television have been identified as novel protective factors against PD. The integration of phenotypic and genomic data may help to identify risk factors and prevention targets for PD.

Air Pollution and Parkinson Disease in a Population-Based Study

The role of air pollution in risk and progression of Parkinson disease (PD) is unclear. To assess whether air pollution is associated with increased risk of PD and clinical characteristics of PD. This population-based case-control study included patients with PD and matched controls from the Rochester Epidemiology Project from 1998 to 2015. Data were analyzed from January to June 2024. Mean annual exposure to particulate matter with a diameter of 2.5 µm or less (PM2.5) from 1998 to 2015 and mean annual exposure to nitrogen dioxide (NO2) from 2000 to 2014. Outcomes of interest were PD risk, all-cause mortality, presence of tremor-predominant vs akinetic rigid PD, and development of dyskinesia. Models were adjusted for age, sex, race and ethnicity, year of index, and urban vs rural residence. A total of 346 patients with PD (median [IQR] age 72 [65-80] years; 216 [62.4%] male) were identified and matched on age and sex with 4813 controls (median [IQR] age, 72 [65-79] years, 2946 [61.2%] male). Greater PM2.5 exposure was associated with increased PD risk, and this risk was greatest after restricting to populations within metropolitan cores (odds ratio [OR], 1.23; 95% CI, 1.11-1.35) for the top quintile of PM2.5 exposure compared with the bottom quintile. Greater NO2 exposure was also associated with increased PD risk when comparing the top quintile with the bottom quintile (OR, 1.13; 95% CI, 1.07-1.19). Air pollution was associated with a 36% increased risk of akinetic rigid presentation (OR per each 1-μg/m3 increase in PM2.5, 1.36; 95% CI, 1.02-1.80). In analyses among patients with PD only, higher PM2.5 exposure was associated with greater risk for developing dyskinesia (HR per 1-μg/m3 increase in PM2.5, 1.42; 95% CI, 1.17-1.73), as was increased NO2 exposure (HR per 1 μg/m3 increase in NO2, 1.13; 95% CI, 1.06-1.19). There was no association between PM2.5 and all-cause mortality among patients with PD. In this case-control study of air pollution and PD, higher levels of PM2.5 and NO2 exposure were associated with increased risk of PD; also, higher levels of PM2.5 exposure were associated with increased risk of developing akinetic rigid PD and dyskinesia compared with patients with PD exposed to lower levels. These findings suggest that reducing air pollution may reduce risk of PD, modify the PD phenotype, and reduce risk of dyskinesia.

The Associations Among Gut Microbiota, Branched Chain Amino Acids, and Parkinson's Disease: Mendelian Randomization Study.

In experimental and observational studies, the characteristics of gut microbiota have been associated with Parkinson's disease (PD), among which metabolic pathways played an important role. However, the causality remained unclear. Herein, we aimed to determine the potential impact of gut microbiota and gut microbiota-derived metabolites on PD risk using a Mendelian randomization (MR) approach. We included as exposures gut microbial taxa abundance and gut-derived metabolites (branched chain amino acids [BCAAs]), with PD as the outcome. In addition, we explored whether BCAAs act as a mediating factor in the pathway from gut microbiota to PD. We found evidence of a causality of 15 microbial taxa and PD before and after sensitivity analyses, but not after multiple testing correction. There was significant association between BCAAs levels and the risk of PD, especially isoleucine (OR = 0.995, 95% CI 0.992-0.999, p = 0.004, pFDR = 0.012). In addition, the causality of gut microbiota and BCAAs was also explored that the increased g_Coprococcus abundance can result in the decrease in isoleucine level (OR = 1.046; 95% CI, 1.009-1.085; p = 0.016). Our findings indicated suggestive association between gut microbiota and its metabolites and PD. Furthermore, higher BCAAs levels were associated with the decreased PD risk. This study may provide new targets for PD treatment, such as dietary BCAAs supplementation.

Unmet Need in Early-Onset Parkinson's Disease: Deep Brain Stimulation and Pregnancy.

Pregnancy in women with early-onset Parkinson's disease (PD) is likely to have a higher frequency given the trend toward increasing maternal age, thus resulting in a greater overlap time between childbearing age and PD risk. Deep brain stimulation (DBS) therapy is nowadays offered to PD patients at earlier stage of the disease, when women can still be pre-menopausal. However, few data are available about DBS safety during pregnancy. From a review of the available literature, only one article was published on this topic so far. Therefore, we have developed a clinical consensus on the safety of DBS during pregnancy in PD patients.

The association between cigarette smoking and dementia with Lewy bodies

IntroductionCigarette smoking is associated with a reduced risk of Parkinson's disease (PD). As dementia with Lewy bodies (DLB) and PD share core neuropathologic features, we set out to examine the relationship between smoking and DLB. MethodsDiagnosis at baseline visit and smoking history of participants ≥50 years old in the National Alzheimer's Coordinating Center (NACC) cohort were evaluated in this cross-sectional study. Odds of diagnosis of cognitive impairment due to DLB, PD, vascular dementia (VD), or Alzheimer's disease (AD) compared to normal cognition based on smoking status and duration were determined using logistic regression. Results37,478 participants were included (mean age 72 years (SD 9), 57 % female). The odds of DLB were reduced in all smoking status groups compared to never smokers (OR (95 % CI)): ever smokers 0.850 (0.745–0.971), former smokers 0.871 (0.761–0.997), current smokers 0.640 (0.419–0.947)) and in all smoking duration groups. As expected, the odds of PD were reduced in all smoking groups and fell with longer smoking duration. The odds of VD were increased in the current smoking group and rose with greater smoking duration. The odds of AD were unchanged in current smokers, decreased in ever and former smokers, and increased with longer cumulative smoking duration. ConclusionsCigarette smoking is associated with lower odds of diagnosis of DLB at baseline visit in the NACC cohort. In the context of the well-established reduced risk of PD among smokers, this preliminary evidence of a potential protective effect of smoking on DLB warrants further study.

The diagnostic value of neutrophil to lymphocyte ratio, albumin to fibrinogen ratio, and lymphocyte to monocyte ratio in Parkinson's disease: a retrospective study.

Parkinson's disease (PD) is a prevalent disorder of the central nervous system, marked by the degeneration of dopamine (DA) neurons in the ventral midbrain. In the pathogenesis of PD, inflammation hypothesis has been concerned. This study aims to investigate clinical indicators of peripheral inflammation in PD patients and to explore the diagnostic value of neutrophil-to-lymphocyte ratio (NLR), albumin-to-fibrinogen ratio (AFR), and lymphocyte-to-monocyte ratio (LMR) in assessing PD risk. This study included 186 patients with PD and 201 matched healthy controls (HC) with baseline data. Firstly, the differences of hematological indicators between PD group and healthy participants were compared and analyzed. Univariate and multivariate regression analyses were then conducted. Smooth curve fitting was applied to further validate the relationships between NLR, LMR, AFR, and PD. Subsequently, subgroup analysis was conducted in PD group according to different duration of disease and Hoehn and Yahr (H&Y) stage, comparing differences in clinical indicators. Finally, the receiver operating characteristic (ROC) curve was employed to assess the diagnostic value of NLR, LMR, and AFR in PD. Compared to the HC group, the PD group showed significantly higher levels of hypertension, diabetes, neutrophil count, monocyte count, CRP, homocysteine, fibrinogen, and NLR. Conversely, levels of LMR, AFR, lymphocyte count, HDL, LDL, TG, TC, uric acid, and albumin were significantly lower. The multivariate regression model indicated that NLR (OR = 1.79, 95% CI: 1.39-2.31, p < 0.001), LMR (OR = 0.75, 95% CI: 0.66-0.85, p < 0.001), and AFR (OR = 0.79, 95% CI: 0.73-0.85, p < 0.001) were significant factors associated with PD. Smooth curve fitting revealed that NLR was positively linked to PD risk, whereas AFR and LMR were inversely associated with it. In ROC curve analysis, the AUC of AFR was 0.7290, the sensitivity was 63.98%, and the specificity was 76.00%. The AUC of NLR was 0.6200, the sensitivity was 50.54%, and the specificity was 71.50%. The AUC of LMR was 0.6253, the sensitivity was 48.39%, and the specificity was 73.00%. The AUC of the combination was 0.7498, the sensitivity was 74.19%, and the specificity was 64.00%. Our findings indicate that NLR, LMR, and AFR are significantly associated with Parkinson's disease and may serve as diagnostic markers.

Total physical activity, plant-based diet and neurodegenerative diseases: A prospective cohort study of the UK biobank

IntroductionNeurodegenerative diseases (NDDs) result from a complex interplay of genetic, environmental and aging factors. A balanced diet and adequate physical activity (PA) are recognized as pivotal components among modifiable environmental factors. The independent impact on NDD incidence has been previously debated. This investigation seeks to delineate the association between PA and NDDs across various levels of adherence to a plant-based diet. MethodsIn this study, a cohort of 368,934 participants from the UK Biobank was analyzed. Total physical activity (TPA) levels and healthful plant-based diet index (hPDI) were calculated and categorized. A multiple adjusted Cox model was utilized to evaluate the influence of TPA and hPDI on common NDDs, respectively. ResultsFinally, 4602 identified cases diagnosed as Alzheimer's disease (AD), Parkinson's disease (PD) or amyotrophic lateral sclerosis (ALS). We found that higher TPA was significantly associated with a reduced risk of developing AD (Q3: HR 0.87; Q4: HR 0.78) and PD (Q3: HR 0.86; Q4: HR 0.81). The protective effect was further accentuated with adherence to a plant-based diet. However, these connections were not observed in the analysis of ALS regardless of dietary patterns. ConclusionOur findings underscore a significant association between higher TPA and reduced risks of AD and PD, with an enhanced effect observed in conjunction with a plant-based diet. This study contributes to addressing the knowledge gap regarding the combined impact of TPA and a plant-based diet on NDDs occurrence, providing insights into potential underlying mechanisms.

The Impact of Diet on Parkinson's Disease: A Systematic Review.

Parkinson's disease (PD) is a progressive neurodegenerative disorder with complex etiology. Emerging evidence suggests that diet may play a role in PD risk, progression, and symptom management. However, the relationship between dietary factors and PD remains poorly understood. This systematic review aimed to synthesize and evaluate the current evidence on the associations between dietary patterns, specific nutrients, and PD risk, progression, and symptom management. We conducted a comprehensive literature search in major databases for studies published up to 2024. Eligible studies included prospective cohorts, case-control studies, randomized controlled trials, and cross-sectional analyses investigating the relationship between diet and PD. Data extraction and quality assessment were performed independently by two reviewers. Eleven studies met the inclusion criteria. Adherence to healthy dietary patterns, particularly those rich in fruits, vegetables, whole grains, and fish, was consistently associated with reduced PD risk. Conversely, Western-style diets high in processed foods and red meat were linked to increased risk. Specific nutrients, including antioxidants and vitamins K and C, showed potential neuroprotective effects, while high iron intake was associated with increased PD risk. Diet quality was found to influence PD symptoms, particularly non-motor symptoms like constipation. Emerging evidence suggested a role for the gut microbiome in mediating diet-PD relationships. Specialized diets, such as ketogenic and low-carbohydrate diets, showed promise in managing PD symptoms in small-scale studies. This review provides evidence for the significant role of diet in PD risk, progression, and symptom management. Dietary interventions have the potential to serve as complementary approaches to existing PD therapies. However, the complex nature of the diet-PD relationship necessitates further research, particularly well-designed long-term randomized controlled trials, to develop evidence-based, personalized dietary recommendations for PD prevention and management.